H100 SXM5 on Voltage Park
Visit Voltage ParkVoltage Park emerges as a powerhouse in GPU cloud computing with its colossal 24,000 NVIDIA H100 SXM5 GPUs, supported by a non-profit dedicated to enabling large-scale AI training. This offering targets ML engineers and data scientists at research labs, AI startups, and enterprises pursuing frontier models requiring thousands of GPUs for distributed training. The H100 SXM5, built on Hopper architecture with 80GB HBM3 VRAM, delivers breakthrough performance: up to 4x faster AI training than A100 via Transformer Engine, 1979 TFLOPS FP16, and 3958 TFLOPS FP8. Voltage Park's per-hour billing model offers flexibility for bursty workloads without infrastructure ownership. What makes this combo noteworthy is unmatched scale—rivaling supercomputers—combined with non-profit stability for reliable access during peak demand. Key value propositions include seamless multi-node scaling, high-bandwidth interconnects optimized for massive clusters, and mission-driven focus on open AI advancement. While detailed benchmarks are emerging, this positions Voltage Park as ideal for exascale training of 100B+ parameter models, democratizing access to elite compute.
Why NVIDIA H100 SXM5 on Voltage Park?
Opt for Voltage Park's H100 SXM5 when your AI training demands unprecedented scale: a 24k-GPU fleet dwarfs competitors, enabling cluster sizes infeasible elsewhere. Non-profit backing ensures operational stability, cost predictability, and potential alignment perks for open research projects. This pairing amplifies the H100's strengths—NVLink 900GB/s intra-node, InfiniBand-ready for inter-node—with infrastructure tailored for low-latency collectives in massive distributed jobs. Per-hour billing suits variable-duration runs, avoiding underutilization penalties of smaller providers. Unlike fragmented fleets, Voltage Park minimizes scheduling delays for 1k+ GPU allocations, excelling in bottlenecks like all-reduce for trillion-parameter models. Ideal for teams prioritizing raw TFLOPS at scale over niche customizations.
Live Pricing
Real-time NVIDIA H100 SXM5 offers from Voltage Park
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 930GB RAM 99800GB Storage | Dallas, Texas | $1.89/GPU/hr $15.12/hr total (8×) | |||
Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 930GB RAM 99800GB Storage | Dallas, Texas | $1.89/GPU/hr $15.12/hr total (8×) | |||
Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 960GB RAM 99800GB Storage | Dallas, Texas | $1.89/GPU/hr $15.12/hr total (8×) | |||
Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 960GB RAM 99800GB Storage | Dallas, Texas | $1.89/GPU/hr $15.12/hr total (8×) | |||
Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 960GB RAM 14580GB Storage | Dallas, Texas | $1.89/GPU/hr $15.12/hr total (8×) |
Performance Notes
Voltage Park's H100 SXM5 delivers peak Hopper specs: 80GB HBM3 at 3.35TB/s bandwidth, 1979 TFLOPS TF32, excelling in transformer training with FP8/INT8 precision. Expect strong multi-GPU scaling via NVLink within nodes (up to 8x) and cluster-wide via high-speed fabrics—likely 400-800Gb/s InfiniBand—for efficient NCCL all-reduces at 10k+ GPUs. Massive 24k fleet suggests optimized topology for linear scaling, akin to DGX SuperPODs. Storage likely includes fast NVMe local SSDs; shared HPC options probable but unconfirmed. No public benchmarks yet—performance hinges on software stack (CUDA 12+, PyTorch DDP). Preemptions unknown; test small clusters first for real-world MFU.
A provider operating a massive fleet of H100s backed by a non-profit for large-scale training.
Best For
Unique Features
- 24k H100 fleet
- Non-profit backing
VRAM
80GB
Architecture
Hopper
Tier
enterprise
Platform Features
Getting Started
Launching NVIDIA H100 SXM5 on Voltage Park is streamlined for scale-focused users. Register, select from the 24k H100 pool, configure cluster size and env, then deploy. Per-hour billing activates on launch; access via SSH/Jupyter. Non-profit vetting may apply for large allocations.
Steps
- 1Sign up on Voltage Park site; submit project details for non-profit verification (1-2 days).
- 2In console, select H100 SXM5, specify GPU/node count (1-24k), and instance type.
- 3Choose image (Ubuntu/CUDA 12.x, preloaded PyTorch/TensorFlow) and add storage/network configs.
- 4Review per-hour costs, confirm billing, and launch cluster (provisions in minutes for small, hours for massive).
- 5Connect via SSH keys or web console; run jobs with Slurm/Kubernetes for orchestration.
Pro Tips
- Tune NCCL for InfiniBand ( NCCL_IB_DISABLE=0 ) to hit peak inter-node bandwidth on large clusters.
- Apply for non-profit grants if open-source aligned; secures priority during high-demand periods.
- Profile MFU early with small runs—per-hour model rewards optimized, long-haul training jobs.
Frequently Asked Questions
What is Voltage Park's billing model for NVIDIA H100 SXM5?▾
Voltage Park bills per-hour for GPU instances including NVIDIA H100 SXM5. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Voltage Park offer spot instances for NVIDIA H100 SXM5?▾
No, Voltage Park does not currently offer spot instances for NVIDIA H100 SXM5. All instances are billed at on-demand rates. However, they do offer reserved instances for committed usage, which can provide significant discounts for long-term workloads.
Does Voltage Park offer reserved instances for NVIDIA H100 SXM5?▾
Yes, Voltage Park offers reserved instance pricing for NVIDIA H100 SXM5, which can provide significant discounts (typically 20-40% off on-demand rates) for committed usage periods. Reserved instances are ideal for predictable, long-running workloads like production inference services, ongoing training pipelines, or development environments that run continuously. Contact Voltage Park for current reserved pricing and commitment terms.